Dear JTS Readers,
As guest editors Keith Ord and Peg Young point out, forecasting is at the heart of policymaking. To make policy, one must forecast what will happen if current policies continue, and one must then forecast what will happen if policies change. The papers in this issue give policymakersand those who provide analysis for thema variety of approaches to forecasting outcomes under various policy scenarios.
The structural forecasting models offer the most complex analysis of the interaction of the various factors in the evolution of a policy outcome, and are helpful in analyzing what happens when several policy variables are changing simultaneously. Auto-regressive models, like ARIMA, sometimes perform better as pure forecasting models, in the sense that they often can produce exceptionally high predictive accuracy and are particularly well-suited to modeling the influence of interventions of varying degrees of duration.
In some cases, the models are useful not so much for forecasting the future, but for "forecasting" the presentor even the past. The Liu and Vilain paper shows how a forecasting model can be employed to estimate data at a more disaggregated geographical level than the reported data permit. In the world of transportation data, where the water glass of data often seems more empty than full, this application of forecasting may be extremely valuable.
The application of forecasting to policymaking will be of even greater interest to me as I leave the Bureau of Transportation Statistics (BTS) to take a new position as Chief Economist in DOT's Office of Policy. The Department is investigating a variety of policy proposalstruck-only lanes, congestion pricing, and increased private sector financing of transportation infrastructure, for exampleand forecasting techniques will be essential in determining the likely effects of these proposals.
Editing a journal is a wonderful intellectual experience, and I leave the editorship with considerable regret. I will continue to participate as one of the journal's family of reviewers and readers and will continue to make use of the journal's papers in my work. Just this month, for example, I used the estimates of price-elasticities of demand for tolled highways that Anna Matas and José-Luis Raymond presented in their recent article in volume 6 numbers 2/3. Congestion pricing is a topic of considerable interest in the policymaking circles of the Department of Transportation.
I am delighted that I leave the Journal of Transportation and Statistics in the capable hands of Peg Young as Editor-in-Chief and Marsha Fenn as Managing Editor. Peg has worked closely with me as Associate Editor, and we have educated each other in economics and statistics in a mutually edifying partnership. Marsha Fenn, of course, has been with JTS since the beginning, and the high quality of the journal is primarily due to her hard work, painstaking thoroughness, and high standards. Peg and Marsha will be assisted by David Chien and Caesar Singh as Associate Editors, by Jennifer Brady as the Data Review Editor, and by Alpha Glass as the Editorial Assistant.
I want to thank the members of the JTS Editorial Board, our reviewers, our authors, and our readers, along with the staff, for making my work on the journal such an enjoyable experience. I look forward to joining our readership and benefiting from the work of our new editorial staff.
JOHN V. WELLS